README: Regression model of frequency-dependent selection

Source codes and data of Sato et al. "Detecting frequency-dependent selection through the effects of genotype similarity on fitness components". A vignette-style instruction is available in Rmarkdown and its output HTML as index.Rmd and index.html, respectively (see also <https://yassato.github.io/RegressionFDS/> for viewing). A developer version is available at <https://github.com/yassato/RegressionFDS>.

application

This directory includes source codes and/or input data for empirical analyses on Arabidopsis halleri, Ischnura elegans, and Arabidopsis thaliana, proceeding as follows.

GLMM analysis of Arabidopsis halleri

• Ahal_FieldSurvey.R\ Poisson GLMM of the flower number in wild Arabidopsis halleri in a natural population. Data are available via Dryad repository (<https://doi.org/10.5061/dryad.53k2d>).

GLMM analysis of Ischnura elegans

• damselfly_cage_data.R\ Poisson GLMM of the egg number in Ischnura elegans in semi-field cages. The original data are generated by Takahashi et al. (2014) Nature Communications 5:4468.

Branch number GWAS in Arabidopsis thaliana

• pheno_branchNum.csv\
  Accession list and phenotype data as an input file for "BranchNo2019GWAS.R", including the following columns.

  • IndivID: Plant ID
  • Name: Name of the accession
  • Source: CS number of ABRC seed stock
  • gwasID: GWAS genotype ID assigned to the accession
  • Block: Experimental block ID
  • position_X: cell-tray position along x-axis within a block
  • position_Y: cell-tray position along y-axis within a block
  • edge: Edge of the block (1) or not (0).
  • InitLeafLen: The length of largest leaf at the start of field experiment
  • Bolting: Presence (1) or absence (0) of inflorescence 2 wk after the start of experiment
  • BranchNo: No. of reproductive branches. Dead plants are considered zero numbers.

• subsetSNP.py\
  Python script to extract genotype data from .hdf available at AraGWAS Catalog (<https://aragwas.1001genomes.org>).

• reshapeSNP.R\
  R script to prepare genotype data for for "BranchNo2019GWAS.R" after subsetSNP.py.

• BranchNo2019GWAS.R\
  Field GWAS of the branch number using 199 accessions of A. thaliana.

• BranchNo2019GWASfigure.R\
  Manhattan and QQ plots for the output from "BranchNo2019GWAS.R".

simulation

This directory includes source codes for simulations, numerical examples, and their figure presentation, proceeding as follows.

Ising model simulation

• IsingGenoWeighted.R\ R script for the forward Ising simulation when transition probabilities follow Mendelian inheritance.

Fitness function

• AsymFDSfitnessFunctions.R\ Numerical analysis and figure presentation for fitness functions in response to allele frequency.

GWAS simulation

• SLiM codes (xxxx.slim) for forward genetic simulations of negative frequency-dependent selection (NFDS); positive frequency-dependent selection (PFDS); overdominance (OD); and spatiotemporally varying selection (STVS).
• outputSLiM_and_GWAS.R GWAS simulation and power analysis using the SLiM output.
• outputFigures.R\ Figure presentations for the GWAS simulation.
• /output\ A folder to save SLiM and R outputs, including the following input data for the vignette (index.Rmd)
  • toy1.rds: Single-locus example data with split subpopulations
  • toy2.rds: Single-locus example data with continuous space
  • toy3.rds: GWAS example with with split subpopulations
  • toy4.rds: GWAS example with with continuous space

Vignette

• toydata.R\ R script to create input toy data for index.Rmd in the top directory